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. 2022 Sep 22;28(11):2309–2320. doi: 10.1038/s41591-022-01980-3

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Extended Data Fig. 6 — a) Adjusted trajectories representing the partial cumulative risk dependent on the metabolomic state over time for the endpoints where the metabolomic state added information to the Age+Sex baseline (see Fig. 3b) for the bottom (light blue), median (blue), and top (dark blue) 10% metabolomic state quantiles. The shaded area indicates the 95% confidence interval as estimated by bootstrapping over 1000 iterations. b) Adjusted hazard ratios (HRs) for the metabolomic state in combination with the three clinical predictor sets. A unit standard deviation increase in the metabolomic state corresponds to an HR increase in predicted risk. Statistical measures were derived from n = 117.981 individuals. Individuals with prior events were excluded (Supplementary Table 1). Data are presented as median (center of error bar) and 95% CI (line of error bar) determined by bootstrapping with 1000 iterations.